def get_drug_disease_mapping_from_cui(name_to_cui_and_confidences,
name_to_drug, synonym_to_drug,
concept_id_to_mesh_id, mesh_id_to_name,
dump_file):
"""
name_to_cui_and_confidences mapping from MEDI
name_to_drug & synonym mapping from DrugBank
concept & mesh_id mapping from UMLS (MSH | MH)
"""
if dump_file is not None and os.path.exists(dump_file):
drug_to_diseases = cPickle.load(open(dump_file))
return drug_to_diseases
drug_to_diseases = {} # (mesh_term, mesh_id, association score)
for name, values in name_to_cui_and_confidences.iteritems():
# Get drugbank id from name in the label
drugbank_id, drugbank_name = parse_drugbank.get_drugbank_id_from_name(
name, name_to_drug, synonym_to_drug)
if drugbank_id is None:
continue
print "%s\t%s\t%s" % (drugbank_name, drugbank_id, name)
for cui, val in values:
#print cui, val, cui in concept_id_to_mesh_id
if cui in concept_id_to_mesh_id:
dui = concept_id_to_mesh_id[cui]
phenotype = mesh_id_to_name[dui]
drug_to_diseases.setdefault(drugbank_id, set()).add(
(phenotype, dui, val))
if dump_file is not None:
cPickle.dump(drug_to_diseases, open(dump_file, 'w'))
return drug_to_diseases
def get_drug_disease_mapping(spl_id_to_cuis, spl_id_to_names, name_to_drug, synonym_to_drug, concept_id_to_mesh_id, mesh_id_to_name, dump_file):
"""
spl_id_to_cuis mapping from LabeledIn
spl_id_to_names mapping from DailyMed rxnorm
name_to_drug & synonym mapping from DrugBank
concept & mesh_id mapping from UMLS (MSH | MH)
"""
if os.path.exists(dump_file):
drug_to_diseases = cPickle.load(open(dump_file))
return drug_to_diseases
drug_to_diseases = {} # (mesh_id, mesh_term, association score)
val = 1
for spl_id, cuis in spl_id_to_cuis.iteritems():
if spl_id not in spl_id_to_names:
continue
for name in spl_id_to_names[spl_id]:
# Get drugbank id from name in the label
if name.find(" / ") != -1: # Skip drug combinations
continue
drugbank_id, drugbank_name = parse_drugbank.get_drugbank_id_from_name(drug, name_to_drug, synonym_to_drug, regex_db_name = True)
if drugbank_id is not None:
break
if drugbank_id is None:
continue
print "%s\t%s\t%s\t%s" % (spl_id, drugbank_id, drugbank_name, name)
for cui in cuis:
if cui in concept_id_to_mesh_id:
dui = concept_id_to_mesh_id[cui]
phenotype = mesh_id_to_name[dui]
drug_to_diseases.setdefault(drugbank_id, set()).add((phenotype, dui, val))
cPickle.dump(drug_to_diseases, open(dump_file, 'w'))
return drug_to_diseases
def get_drug_disease_mapping_from_cui(name_to_cui_and_confidences, name_to_drug, synonym_to_drug, concept_id_to_mesh_id, mesh_id_to_name, dump_file):
"""
name_to_cui_and_confidences mapping from MEDI
name_to_drug & synonym mapping from DrugBank
concept & mesh_id mapping from UMLS (MSH | MH)
"""
if dump_file is not None and os.path.exists(dump_file):
drug_to_diseases = cPickle.load(open(dump_file))
return drug_to_diseases
drug_to_diseases = {} # (mesh_term, mesh_id, association score)
for name, values in name_to_cui_and_confidences.iteritems():
# Get drugbank id from name in the label
drugbank_id, drugbank_name = parse_drugbank.get_drugbank_id_from_name(name, name_to_drug, synonym_to_drug)
if drugbank_id is None:
continue
print "%s\t%s\t%s" % (drugbank_name, drugbank_id, name)
for cui, val in values:
#print cui, val, cui in concept_id_to_mesh_id
if cui in concept_id_to_mesh_id:
dui = concept_id_to_mesh_id[cui]
phenotype = mesh_id_to_name[dui]
drug_to_diseases.setdefault(drugbank_id, set()).add((phenotype, dui, val))
if dump_file is not None:
cPickle.dump(drug_to_diseases, open(dump_file, 'w'))
return drug_to_diseases
def get_drug_disease_mapping(name_to_icd_and_confidences, name_to_drug,
synonym_to_drug, icd_to_mesh_ids, mesh_id_to_name,
dump_file):
"""
name_to_icd_and_confidences mapping from MEDI
name_to_drug & synonym mapping from DrugBank
icd_to_mesh_ids mapping from DO
mesh_id_to_name mapping from UMLS (MSH | MH)
"""
if dump_file is not None and os.path.exists(dump_file):
drug_to_diseases = cPickle.load(open(dump_file))
return drug_to_diseases
drug_to_diseases = {} # (mesh_term, mesh_id, association score)
for name, values in name_to_icd_and_confidences.iteritems():
#if name != "Acarbose":
# continue
# Get drugbank id from name in the label
drugbank_id, drugbank_name = parse_drugbank.get_drugbank_id_from_name(
name, name_to_drug, synonym_to_drug)
if drugbank_id is None:
continue
#if drugbank_id != "DB00284":
# continue
#print "%s\t%s\t%s" % (drugbank_name, drugbank_id, name)
for icd, val in values:
icd = icd.split(".")[0]
#print icd, val, icd in icd_to_mesh_ids
if icd in icd_to_mesh_ids:
dui_list = icd_to_mesh_ids[icd]
#print dui_list
for dui in dui_list:
if dui not in mesh_id_to_name:
continue
phenotype = mesh_id_to_name[dui].lower()
#print dui, phenotype
drug_to_diseases.setdefault(drugbank_id, set()).add(
(phenotype, dui, val))
#else:
# ICD9 ids are problematic - consider name matching
if dump_file is not None:
cPickle.dump(drug_to_diseases, open(dump_file, 'w'))
return drug_to_diseases
def get_drug_disease_mapping(name_to_icd_and_confidences, name_to_drug, synonym_to_drug, icd_to_mesh_ids, mesh_id_to_name, dump_file):
"""
name_to_icd_and_confidences mapping from MEDI
name_to_drug & synonym mapping from DrugBank
icd_to_mesh_ids mapping from DO
mesh_id_to_name mapping from UMLS (MSH | MH)
"""
if dump_file is not None and os.path.exists(dump_file):
drug_to_diseases = cPickle.load(open(dump_file))
return drug_to_diseases
drug_to_diseases = {} # (mesh_term, mesh_id, association score)
for name, values in name_to_icd_and_confidences.iteritems():
#if name != "Acarbose":
# continue
# Get drugbank id from name in the label
drugbank_id, drugbank_name = parse_drugbank.get_drugbank_id_from_name(name, name_to_drug, synonym_to_drug)
if drugbank_id is None:
continue
#if drugbank_id != "DB00284":
# continue
#print "%s\t%s\t%s" % (drugbank_name, drugbank_id, name)
for icd, val in values:
icd = icd.split(".")[0]
#print icd, val, icd in icd_to_mesh_ids
if icd in icd_to_mesh_ids:
dui_list = icd_to_mesh_ids[icd]
#print dui_list
for dui in dui_list:
if dui not in mesh_id_to_name:
continue
phenotype = mesh_id_to_name[dui].lower()
#print dui, phenotype
drug_to_diseases.setdefault(drugbank_id, set()).add((phenotype, dui, val))
#else:
# ICD9 ids are problematic - consider name matching
if dump_file is not None:
cPickle.dump(drug_to_diseases, open(dump_file, 'w'))
return drug_to_diseases
def get_drug_disease_mapping(spl_id_to_cuis, spl_id_to_names, name_to_drug,
synonym_to_drug, concept_id_to_mesh_id,
mesh_id_to_name, dump_file):
"""
spl_id_to_cuis mapping from LabeledIn
spl_id_to_names mapping from DailyMed rxnorm
name_to_drug & synonym mapping from DrugBank
concept & mesh_id mapping from UMLS (MSH | MH)
"""
if os.path.exists(dump_file):
drug_to_diseases = cPickle.load(open(dump_file))
return drug_to_diseases
drug_to_diseases = {} # (mesh_id, mesh_term, association score)
val = 1
for spl_id, cuis in spl_id_to_cuis.iteritems():
if spl_id not in spl_id_to_names:
continue
for name in spl_id_to_names[spl_id]:
# Get drugbank id from name in the label
if name.find(" / ") != -1: # Skip drug combinations
continue
drugbank_id, drugbank_name = parse_drugbank.get_drugbank_id_from_name(
drug, name_to_drug, synonym_to_drug, regex_db_name=True)
if drugbank_id is not None:
break
if drugbank_id is None:
continue
print "%s\t%s\t%s\t%s" % (spl_id, drugbank_id, drugbank_name, name)
for cui in cuis:
if cui in concept_id_to_mesh_id:
dui = concept_id_to_mesh_id[cui]
phenotype = mesh_id_to_name[dui]
drug_to_diseases.setdefault(drugbank_id, set()).add(
(phenotype, dui, val))
cPickle.dump(drug_to_diseases, open(dump_file, 'w'))
return drug_to_diseases
